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Robust model reference adaptive controller for 3-DOF planar manipulator.

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Automation

Background:

  • Industrial automation relies on precise motion control of robotic manipulators.
  • The nonlinear and coupled dynamics of three-link robotic manipulators present significant control challenges.
  • Conventional control methods struggle with external disturbances and parametric uncertainties.

Purpose of the Study:

  • To introduce a novel decoupling technique for simplifying complex robotic manipulator dynamics.
  • To design and evaluate a robust Model Reference Adaptive Controller (MRAC) for enhanced trajectory tracking.
  • To address the limitations of conventional MRAC in the presence of uncertainties and disturbances.

Main Methods:

  • Developed a decoupling technique modeling joint acceleration based on individual torque and velocity.
  • Derived simplified decoupled state-space equations for the three-link manipulator.
  • Designed a robust MRAC incorporating uncertainty and disturbance compensation.

Main Results:

  • The proposed decoupling technique simplifies manipulator dynamics.
  • The robust MRAC demonstrated superior performance over the conventional MRAC.
  • Accurate trajectory tracking and stability were maintained under uncertainty and external disturbances.

Conclusions:

  • The robust MRAC offers a significant improvement for controlling nonlinear robotic systems.
  • The decoupling approach effectively manages complex manipulator dynamics.
  • This enhanced control strategy is vital for improving productivity and efficiency in industrial automation.